R Notebook

library(leaflet)
library(readxl)
library(dplyr)
library(reticulate)

maindata <- read_excel("Documents/Spring2021/DataVisualization/Project/maindata.xlsx")

Error: `path` does not exist: ‘Documents/Spring2021/DataVisualization/Project/maindata.xlsx’

Let look at how many unique values each column has

sapply(maindata, function(x) length(unique(x)))

                    id              log_price          property_type              room_type              amenities 
                 74111                    767                     35                      3                  67122 
          accommodates              bathrooms               bed_type    cancellation_policy           cleaning_fee 
                    16                     18                      5                      5                      2 
                  city            Description           first_review   host_has_profile_pic host_identity_verified 
                     6                  73469                   2555                      3                      3 
    host_response_rate             host_since       instant_bookable            last_review                    lat 
                    81                   3088                      2                   1372                  74058 
                  long                   name          neighbourhood      number_of_reviews   review_scores_rating 
                 73973                  73331                    620                    371                     55 
         thumbnail_url                zipcode               bedrooms                   beds 
                 65884                    669                     12                     19 

library(ggplot2)
maindata%>% ggplot( aes(x=cancellation_policy, y=log_price))+ geom_boxplot()+ ggtitle( "Boxplot for log_price vs cancellation policy")

Do some hypothesis testing.

First, let us plot the different properties, using the latitude and longitude information given in our dataset.

m <- leaflet(tmp) %>%
addTiles() %>%
addProviderTiles("OpenStreetMap.BZH") %>%
addCircleMarkers(~long, ~lat, color = "red",
stroke=FALSE)
m

From the map above, we can see that the properties listed in our datset are from six different locations: Los Angeles, New York, DC, Boston, Chicago, San Fransico etc.

log_price for th different cities.

NYC

rows = (maindata$city== "NYC") 
tmp = maindata[rows, ]

mybins <- seq(2, 8, by=1.5)
mypalette <- colorBin( palette="YlOrBr",
domain=tmp$log_price,
na.color="transparent",
bins=mybins)

m <- leaflet(tmp) %>%
addTiles() %>%
addProviderTiles("OpenStreetMap.BZH") %>%
addCircleMarkers(~long, ~lat,radius = ~log_price,
fillColor = ~mypalette(log_price),
fillOpacity = 0.5,
color = "white",stroke=FALSE
)%>%
addLegend( pal=mypalette, values=~log_price, opacity=0.9,
title = "Log_price", position = "bottomright" )

Some values were outside the color scale and will be treated as NA

m

Talk about which part of NYC has higher log_price and which part has lowest.

Boston.

rows = (maindata$city== "Boston") 
tmp = maindata[rows, ]

mybins <- seq(2, 8, by=1.5)
mypalette <- colorBin( palette="YlOrBr",
domain=tmp$log_price,
na.color="transparent",
bins=mybins)

m <- leaflet(tmp) %>%
addTiles() %>%
addProviderTiles("OpenStreetMap.BZH") %>%
addCircleMarkers(~long, ~lat,radius = ~log_price,
fillColor = ~mypalette(log_price),
fillOpacity = 0.5,
color = "white",stroke=FALSE
)%>%
addLegend( pal=mypalette, values=~log_price, opacity=0.9,
title = "Log_price", position = "bottomright" )
m

DC

rows = (maindata$city== "DC") 
tmp = maindata[rows, ]

mybins <- seq(2, 8, by=1.5)
mypalette <- colorBin( palette="YlOrBr",
domain=tmp$log_price,
na.color="transparent",
bins=mybins)

m <- leaflet(tmp) %>%
addTiles() %>%
addProviderTiles("OpenStreetMap.BZH") %>%
addCircleMarkers(~long, ~lat,radius = ~log_price,
fillColor = ~mypalette(log_price),
fillOpacity = 0.5,
color = "white",stroke=FALSE
)%>%
addLegend( pal=mypalette, values=~log_price, opacity=0.9,
title = "Log_price", position = "bottomright" )
m

San Francisco.

rows = (maindata$city== "SF") 
tmp = maindata[rows, ]

mybins <- seq(2, 8, by=1.5)
mypalette <- colorBin( palette="YlOrBr",
domain=tmp$log_price,
na.color="transparent",
bins=mybins)

m <- leaflet(tmp) %>%
addTiles() %>%
addProviderTiles("OpenStreetMap.BZH") %>%
addCircleMarkers(~long, ~lat,radius = ~log_price,
fillColor = ~mypalette(log_price),
fillOpacity = 0.5,
color = "white",stroke=FALSE
)%>%
addLegend( pal=mypalette, values=~log_price, opacity=0.9,
title = "Log_price", position = "bottomright" )
m

LA

rows = (maindata$city== "LA") 
tmp = maindata[rows, ]

mybins <- seq(2, 8, by=1.5)
mypalette <- colorBin( palette="YlOrBr",
domain=tmp$log_price,
na.color="transparent",
bins=mybins)

m <- leaflet(tmp) %>%
addTiles() %>%
addProviderTiles("OpenStreetMap.BZH") %>%
addCircleMarkers(~long, ~lat,radius = ~log_price,
fillColor = ~mypalette(log_price),
fillOpacity = 0.5,
color = "white",stroke=FALSE
)%>%
addLegend( pal=mypalette, values=~log_price, opacity=0.9,
title = "Log_price", position = "bottomright" )
m

We can see that along the edge there are properties that are high priced.

Chicago

rows = (maindata$city== "Chicago") 
tmp = maindata[rows, ]

mybins <- seq(2, 8, by=1.5)
mypalette <- colorBin( palette="YlOrBr",
domain=tmp$log_price,
na.color="transparent",
bins=mybins)

m <- leaflet(tmp) %>%
addTiles() %>%
addProviderTiles("OpenStreetMap.BZH") %>%
addCircleMarkers(~long, ~lat,radius = ~log_price,
fillColor = ~mypalette(log_price),
fillOpacity = 0.5,
color = "white",stroke=FALSE
)%>%
addLegend( pal=mypalette, values=~log_price, opacity=0.9,
title = "Log_price", position = "bottomright" )
m

Types of property

rows = (maindata$city== "Chicago") 
tmp = maindata[rows, ]

mybins <- seq(2, 8, by=1.5)
mypalette <- colorBin( palette="YlOrBr",
domain=tmp$property_type,
na.color="transparent",
bins=mybins)

m <- leaflet(tmp) %>%
addTiles() %>%
addProviderTiles("OpenStreetMap.BZH") %>%
addCircleMarkers(~long, ~lat,radius = ~log_price,
fillColor = ~mypalette(property_type),
fillOpacity = 0.5,
color = "white",stroke=FALSE
)%>%
addLegend( pal=mypalette, values=~property_type, opacity=0.9,
title = "Property type", position = "bottomright" )

Error in cut.default(x, binsToUse, labels = FALSE, include.lowest = TRUE,  : 
  'x' must be numeric